Hybrid AI Engineer for Enterprise LLMs & Pipelines

Talentify; Boston (MA); Hybrid; USD 120,000 - 160,000; Full time

Job summary

Talentify seeks an AI Engineer to design, develop, and deploy enterprise AI agents in a hybrid Boston setting. You will collaborate across finance, HR, operations, and safety to standardize AI solutions and deliver measurable business impact.

Responsibilities include building production-ready AI agents, implementing RAG pipelines, and integrating with Teams/SharePoint and Databricks Lakehouse. A strong background in Python, SQL, Databricks, and cross-cloud services is essential.

Qualifications

• 4+ years in AI engineering, data science, or ML-focused software engineering.
• Proven experience building and deploying multiple AI agents in production.
• 2+ years of hands-on experience with LLMs, RAG pipelines, and LLMOps practices.
• Strong proficiency in Python, SQL, and Databricks (Spark/Hadoop equivalents acceptable).

Responsibilities

• Collaborate with corporate functions to identify AI opportunities and standardize across the company.
• Build and deploy production-ready AI agents using Copilot Studio, Power Apps/Automate, ChatGPT Enterprise, or Python-based frameworks.
• Design and operate RAG pipelines with Databricks Delta Tables, Unity Catalog, and Vector Search.
• Implement and maintain integrations across OpenAI, Azure OpenAI, and AWS Bedrock services.
• Partner with Data Engineering to deliver ETL/ELT pipelines, APIs, and event-driven connectors.
• Support onboarding and training for corporate users and field teams, track adoption metrics.
• Produce technical documentation, user stories, and specs for AI solutions.
• Ensure all AI solutions meet data governance, security, and compliance requirements.

Skills

AI engineering

Data science

ML software

Tools

Python

SQL

Databricks

Job description

Talentify seeks an AI Engineer to design, develop, and deploy enterprise AI agents in a hybrid Boston setting. You will collaborate across finance, HR, operations, and safety to standardize AI solutions and deliver measurable business impact.

Responsibilities include building production-ready AI agents, implementing RAG pipelines, and integrating with Teams/SharePoint and Databricks Lakehouse. A strong background in Python, SQL, Databricks, and cross-cloud services is essential.